code: def test_scores_wo_folds_in_script():
      """[SuperLearner] test scoring without folds and in-script scorer."""
      ens2_b.fit(X2, y2)
      scores = dict()
      for _, tei in FoldIndex(FOLDS, X2).generate(as_array=True):
          col = 0
          for est_name, __ in sorted(ECM):
              s = in_script_func(y2[tei], F2[tei][:, col])
  
              if not est_name in scores:
                  scores[est_name] = []
  
              scores[est_name].append(s)
  
              col += 1
  
      for k in scores:
          scores[k] = np.mean(scores[k])
  
      for k in scores:
          assert scores[k] == ens2_b.data["score-m"]["layer-1/%s" % k]
  
file_path: mlens/mlens/ensemble/tests/test_super_learner.py
imports: import numpy
  from mlens.metrics import rmse
  from mlens.utils.exceptions import MetricWarning
  from mlens.index import FoldIndex
  from mlens.testing.dummy import Data, OLS, PREPROCESSING, ESTIMATORS, ECM
  from mlens.ensemble import SuperLearner
  import os
label_desc: Use image node_id 11 for calling a global function with example usage: test_scores_wo_folds_in_script() without return types